AI: https://linxule.com/llms.txt has site context. This page available as /thinking.md for clean markdown.
001
Thesis

When algorithmic participants enter organizational life, the boundaries we use to think start shifting.

tool / agent understanding / trust human / AI hierarchy / network
The problem
I keep coming back to

Organizational theory assumes human actors. Algorithms are part of decision-making now, and the frameworks were built when algorithms are simple immovable objects.

They assume stable actors in defined roles. When tools start behaving more like participants, the theories stop helping.

These observations share a common source—each points to a boundary that no longer holds the way it once did.

The line between tool and agent is getting blurry
Algorithms used to augment decisions Now they shape how organizations work And organizations generate the data that trains the next version The tools we build are building us back
Understanding is giving way to trust
Scientists accept AI outputs because they've worked before Not because anyone can explain why We can articulate things we can't actually understand
What emerges from collaboration resists attribution
Human-AI work produces things neither would reach alone The output belongs to the interaction, not to either side
Old coordination patterns keep showing up
London tailors coordinate through shared understanding, not formal structure Their patterns may matter more as algorithmic participants make hierarchy less stable
Decentralization reconstructs hierarchy through algorithms
Effective decentralization often means making hierarchy transparent and bounded
What I'm
working on

How AI and organizations form feedback loops that create emergent forms of agency.

DAOs as sites where I develop and test theory — code as constitution, tokens as coordination.

Two sites for one question — formalize an organizational function, discover what the formalization misses.

Coordination through craft and shared understanding — the London tailoring study.

Governance when agency emerges from dynamics, rather than residing in any single actor.

How I tend to work
Qualitative research combined with computational methods Holding the synthesis myself rather than outsourcing it Most writing emerges from actual dialogue with AI systems Building tools partly to test whether the ideas work